There is a need to develop improved cytological detection methods for bladder cancer. Several cytologic methods have been utilized for bladder cancer detection, with varying degrees of success. Papanicolaou (PAP) cytology, a currently accepted method, is accurate for only 10 to 50% of low-grade tumors. Flow cytometry yields greater sensitivity and specificity, with a false-positive rate of 2% and a false-negative rate of 18%. Quantitative fluorescence image analysis employs some principles of the other methods, but combines biochemical nucleic acid and visual determinations to increase both sensitivity and specificity, thus reducing false-positive and -negative rates. Because fewer cells are required for each analysis, this method can effectively utilize voided urine samples, contrasted to the greater cell count of bladder washings needed for flow cytometry. This research program is designed to validate and refine a microscope-based quantitative fluorescence method for bladder cancer detection that has shown great promise in comparison to existing methods in preliminary studies. The objective of this proposal is to further validate, in a clinical population that presents with symptoms, the usefulness of the quantitative fluorescence method for detecting DNA aneuploidy. This study is an extension of preliminary studies strongly indicating that acridine orange (AO)-stained urinary sediments can serve to identify malignant or cancer-related cells with excellent reliability, sensitivity, and specificity in both symptomatic and asymptomatic populations. The goal is to validate these preliminary results and to continue a longitudinal study to determine whether quantitative nuclear fluorescence, stoichiometrically related to nuclear nucleic acids, provides earlier bladder cancer detection than is now possible. These studies are important because they offer significantly improved methods for the early detection of bladder cancer, including low-grade tumors. Furthermore, this approach may provide a biochemical method for tumor grading. (3)